Deserialization with pyarrow fails for certain Timestamp-based data frame
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd                                                                      
import pyarrow as pa                                                                     
df = pd.DataFrame([{'Minutes5UTC': '2020-02-25T21:15:00+00:00', 'Minutes5DK': '2020-02-25T22:15:00'}])                                                        
df['Minutes5DK'] = pd.to_datetime(df.Minutes5DK)                                         
df['Minutes5UTC'] = pd.to_datetime(df.Minutes5UTC)                                       
context = pa.default_serialization_context()                                             
pa.deserialize(pa.serialize(df).to_buffer().to_pybytes())
```
#### Problem description
When following the [procedure outlined here](https://stackoverflow.com/a/57986261/5085211) to use `pyarrow` to serialize/deserialize data frames, the above example fails with the following traceback:

```
--------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-9-6f75cc47c6d5> in <module>
----> 1 pa.deserialize(pa.serialize(df).to_buffer().to_pybytes())

~/miniconda3/envs/emission/lib/python3.8/site-packages/pyarrow/serialization.pxi in pyarrow.lib.deserialize()

~/miniconda3/envs/emission/lib/python3.8/site-packages/pyarrow/serialization.pxi in pyarrow.lib.deserialize_from()

~/miniconda3/envs/emission/lib/python3.8/site-packages/pyarrow/serialization.pxi in pyarrow.lib.SerializedPyObject.deserialize()

~/miniconda3/envs/emission/lib/python3.8/site-packages/pyarrow/serialization.pxi in pyarrow.lib.SerializationContext._deserialize_callback()

~/miniconda3/envs/emission/lib/python3.8/site-packages/pyarrow/serialization.py in _deserialize_pandas_dataframe(data)
    167 
    168     def _deserialize_pandas_dataframe(data):
--> 169         return pdcompat.serialized_dict_to_dataframe(data)
    170 
    171     def _serialize_pandas_series(obj):

~/miniconda3/envs/emission/lib/python3.8/site-packages/pyarrow/pandas_compat.py in serialized_dict_to_dataframe(data)
    661 def serialized_dict_to_dataframe(data):
    662     import pandas.core.internals as _int
--> 663     reconstructed_blocks = [_reconstruct_block(block)
    664                             for block in data['blocks']]
    665 

~/miniconda3/envs/emission/lib/python3.8/site-packages/pyarrow/pandas_compat.py in <listcomp>(.0)
    661 def serialized_dict_to_dataframe(data):
    662     import pandas.core.internals as _int
--> 663     reconstructed_blocks = [_reconstruct_block(block)
    664                             for block in data['blocks']]
    665 

~/miniconda3/envs/emission/lib/python3.8/site-packages/pyarrow/pandas_compat.py in _reconstruct_block(item, columns, extension_columns)
    707                                 klass=_int.CategoricalBlock)
    708     elif 'timezone' in item:
--> 709         dtype = make_datetimetz(item['timezone'])
    710         block = _int.make_block(block_arr, placement=placement,
    711                                 klass=_int.DatetimeTZBlock,

~/miniconda3/envs/emission/lib/python3.8/site-packages/pyarrow/pandas_compat.py in make_datetimetz(tz)
    734 def make_datetimetz(tz):
    735     tz = pa.lib.string_to_tzinfo(tz)
--> 736     return _pandas_api.datetimetz_type('ns', tz=tz)
    737 
    738 

TypeError: 'NoneType' object is not callable
```

Perhaps interestingly, if I comment out the two `pd.to_datetime` lines, the thing works (perhaps unsurprisingly), but if I then include them again, the original reproducing example all of a sudden works. That is, this works:

```python
import pandas as pd                                                                      
import pyarrow as pa                                                                     
df = pd.DataFrame([{'Minutes5UTC': '2020-02-25T21:15:00+00:00', 'Minutes5DK': '2020-02-25T22:15:00'}])
context = pa.default_serialization_context()
pa.deserialize(pa.serialize(df).to_buffer().to_pybytes())

df = pd.DataFrame([{'Minutes5UTC': '2020-02-25T21:15:00+00:00', 'Minutes5DK': '2020-02-25T22:15:00'}])
df['Minutes5DK'] = pd.to_datetime(df.Minutes5DK)
df['Minutes5UTC'] = pd.to_datetime(df.Minutes5UTC)
context = pa.default_serialization_context()
pa.deserialize(pa.serialize(df).to_buffer().to_pybytes())
```

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.8.1.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.9.0-11-amd64
machine          : x86_64
processor        : 
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.1
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 45.2.0.post20200210
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.1
IPython          : 7.12.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.1.3
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 0.16.0
pytables         : None
pytest           : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None

</details>
